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Record W2044900847 · doi:10.1002/pros.10179

Quantitation of apoptotic activity following castration in human prostatic tissue in vivo

2002· article· en· W2044900847 on OpenAlexaff
Andrea Staack, Adrienne Kassis, Adam B. Olshen, Yuzhuo Wang, David Wu, Peter R. Carroll, Gary D. Grossfeld, Gerald R. Cunha, Simon W. Hayward

Bibliographic record

VenueThe Prostate · 2002
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteUniversity of California, San Francisco
KeywordsCastrationTUNEL assayProstateApoptosisEpitheliumTerminal deoxynucleotidyl transferaseRenal capsuleAndrogenAndrologyIn vivoOrchiectomyMedicineInternal medicineEndocrinologyBiologyPathologyKidneyCancerHormone

Abstract

fetched live from OpenAlex

BACKGROUND: Androgen deprivation induces apoptosis in the prostate. Representative data, quantitating apoptotic activity in human prostatic epithelium following androgen ablation, are lacking. METHODS: Human prostatic tissue was grafted beneath the renal capsule of intact male athymic mice and allowed to become established. The mice were castrated and specimens were harvested on post-castration day 0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 14, 17, 18, and 21. Tissue was immediately fixed and apoptotic epithelial nuclei were identified. RESULTS: The percentage of terminal deoxynucleotidyl-transferase-mediated dUTP nick end-labeling (TUNEL) positive epithelial cells increased from a baseline of 0.026%, peaked on post-castration day 3 (1.54%), and returned to baseline by day 21. Mathematical analysis predicted that the observed apoptotic activity account for the loss of 87% of prostatic epithelial cells in 3 weeks. CONCLUSIONS: Post-castration apoptosis in human prostatic epithelium was low but was sufficient to account for the loss of nearly 90% of epithelial cells.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.321
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations56
Published2002
Admission routes1
Has abstractyes

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